2020•International Journal of Innovative Technology and Exploring EngineeringOpen access

Development of Prediction Regression Equations for Biomass Estimation in Eucalyptus Forest Plantations in the Punjab State of India

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Abstract

Prediction equations have been worked out on the basis of 17 trees felled for Eucalyptus hybrid for different tree components on the basis of diameter and height (D2 H) which was found to be best suited as depended variable over D & D2 (Diameter at Breast Height 1.37 m). The correlation coefficient (r2 ) values of all the tree components are significant where as these values for AGB (Above Ground Biomass), BGB (Below Ground Biomass) and Total Biomass (TB) is highly significant. These developed prediction equations are validated by comparing the predicted values of total biomass of overall average trees felled with their actual / calculated biomass. The differences of predicted and actual biomass ranged from 6.8 to 38.5 % of different diameter classes in the felled Eucalyptus trees. Generally differences between predicted and actual biomass in percentages of 10 – 30 % is universally acceptable in forest management.

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Prediction equations have been worked out on the basis of 17 trees felled for Eucalyptus hybrid for different tree components on the basis of diameter and height (D2 H) which was found to be best suited as depended variable over D & D2 (Diameter at Breast Height 1.37 m). The correlation coefficient (r2 ) values of all the tree components are significant where as these values for AGB (Above Ground Biomass), BGB (Below Ground Biomass) and Total Biomass (TB) is highly significant. These developed prediction equations are validated by comparing the predicted values of total biomass of overall average trees felled with their actual / calculated biomass. The differences of predicted and actual biomass ranged from 6.8 to 38.5 % of different diameter classes in the felled Eucalyptus trees. Generally differences between predicted and actual biomass in percentages of 10 – 30 % is universally acceptable in forest management.

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Available abstract

Prediction equations have been worked out on the basis of 17 trees felled for Eucalyptus hybrid for different tree components on the basis of diameter and height (D2 H) which was found to be best suited as depended variable over D & D2 (Diameter at Breast Height 1.37 m). The correlation coefficient (r2 ) values of all the tree components are significant where as these values for AGB (Above Ground Biomass), BGB (Below Ground Biomass) and Total Biomass (TB) is highly significant. These developed prediction equations are validated by comparing the predicted values of total biomass of overall average trees felled with their actual / calculated biomass. The differences of predicted and actual biomass ranged from 6.8 to 38.5 % of different diameter classes in the felled Eucalyptus trees. Generally differences between predicted and actual biomass in percentages of 10 – 30 % is universally acceptable in forest management.

Key concepts: Eucalyptus, Biomass (ecology), Diameter at breast height, Mathematics, Regression analysis, Environmental science, Tree (set theory), Coefficient of determination

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Development of Prediction Regression Equations for Biomass Estimation in Eucalyptus Forest Plantations in the Punjab State of India — Research Paper | ScholarLens